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|Title:||Estimating class priors in domain adaptation forword sense disambiguation||Authors:||Chan, Y.S.
|Issue Date:||2006||Citation:||Chan, Y.S.,Ng, H.T. (2006). Estimating class priors in domain adaptation forword sense disambiguation. COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference 1 : 89-96. ScholarBank@NUS Repository.||Abstract:||Instances of a word drawn from different domains may have different sense priors (the proportions of the different senses of a word). This in turn affects the accuracy of word sense disambiguation (WSD) systems trained and applied on different domains. This paper presents a method to estimate the sense priors of words drawn from a new domain, and highlights the importance of using well calibrated probabilities when performing these estimations. By using well calibrated probabilities, we are able to estimate the sense priors effectively to achieve significant improvements in WSD accuracy. © 2006 Association for Computational Linguistics.||Source Title:||COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference||URI:||http://scholarbank.nus.edu.sg/handle/10635/41507||ISBN:||1932432655|
|Appears in Collections:||Staff Publications|
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